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A Project for Monitoring Trends in Burn Severity
Open accessAbstract
Elected officials and leaders of environmental agencies need information about the effects of large wildfires in order to set policy and make management decisions. Recently, the Wildland Fire Leadership Council (WFLC), which implements and coordinates the National Fire Plan (NFP) and Federal Wildland Fire Management Policies (National Fire Plan 2004 ), adopted a strategy to monitor the effectiveness of the National Fire Plan and the Healthy Forests Restoration Act (HFRA). One component of this strategy is to assess the environmental impacts of large wildland fires and identify the trends of burn severity on all lands across the United States. To that end, WFLC has sponsored a six-year project, Monitoring Trends in Burn Severity (MTBS), which requires the U.S. Department of Agriculture Forest Service (USDA-FS) and the U.S. Geological Survey (USGS) to map and assess the burn severity for all large current and historical fires. Using Landsat data and the differenced Normalized Burn Ratio (dNBR) algorithm, the USGS Center for Earth Resources Observation and Science (EROS) and USDA-FS Remote Sensing Applications Center will map burn severity of all fires since 1984 greater than 202 ha (500 ac) in the east, and 404 ha (1,000 ac) in the west. The number of historical fires from this period combined with current fires occurring during the course of the project will exceed 9,000. The MTBS project will generate burn severity data, maps, and reports, which will be available for use at local, state, and national levels to evaluate trends in burn severity and help develop and assess the effectiveness of land management decisions. Additionally, the information developed will provide a baseline from which to monitor the recovery and health of fire-affected landscapes over time. Spatial and tabular data quantifying burn severity will augment existing information used to estimate risk associated with a range of current and future resource threats. The annual report of 2004 fires has been completed. All data and results will be distributed to the public on a Web site.
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“MTBS is currently the best dataset available for the purpose of this analysis, because it contains the largest historical record of CONUS wildland fires larger than 405 ha (1000 acres) in the West, and larger than 202 ha (500 acres) in the East, respectively, between 1984 and 2016.”
From Burned forests impact water supplies (2018) · cites this paper as [27]
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Cites
Photogrammetric Engineering and Remote Sensing
Nicol, J., King, B., Quattrochi, D., Dowman, I. J., Ehlers, M., & Xiaoli, D. (2007) · UCL Discovery (University College London) · Cited by 9,325
Development of a 2001 National Land-Cover Database for the United States
Homer, C. G., Huang, C., Yang, L., Wylie, B. K., & Coan, M. J. (2004) · Photogrammetric Engineering & Remote Sensing · doi:10.14358/pers.70.7.829 · Cited by 1,567
Miller, J. D., & Thode, A. E. (2007) · Remote Sensing of Environment · doi:10.1016/j.rse.2006.12.006 · Cited by 1,444
Remote sensing techniques to assess active fire characteristics and post-fire effects
Lentile, L. B., Holden, Z. A., Smith, A. M. S., Falkowski, M. J., Hudak, A. T., Morgan, P., Lewis, S. A., Gessler, P. E., & Benson, N. (2006) · International Journal of Wildland Fire · doi:10.1071/wf05097 · Cited by 1,002
International Journal of Remote Sensing
(2011) · International Journal of Remote Sensing · doi:10.1080/01431161.2012.638042 · Cited by 1,000
Mapping burns and natural reforestation using thematic Mapper data
García, M. J. L., & Caselles, V. (1991) · Geocarto International · doi:10.1080/10106049109354290 · Cited by 743
FEDERAL FOREST‐FIRE POLICY IN THE UNITED STATES
Stephens, S. L., & Ruth, L. W. (2005) · Ecological Applications · doi:10.1890/04-0545 · Cited by 584
Comparison of burn severity assessments using Differenced Normalized Burn Ratio and ground data
Cocke, A. E., Fulé, P. Z., & Crouse, J. E. (2005) · International Journal of Wildland Fire · doi:10.1071/wf04010 · Cited by 498
Comparison of AVIRIS and Landsat ETM+ detection capabilities for burn severity
van Wagtendonk, J. W., Root, R. R., & Key, C. H. (2004) · Remote Sensing of Environment · doi:10.1016/j.rse.2003.12.015 · Cited by 467
A change detection experiment using vegetation indices.
Lyon, J. G., Yuan, D., Lunetta, R. S., & Elvidge, C. D. (1998) · Cited by 462
Flagged first, then by citations
Research works printed but not linked: 3
- Gmelin, M., and K. Brewer. 2002. Operational change detection-based fire severity mapping using Landsat TM data. P. 1–8 in Rapid delivery of remote sensing products [electronic resource]: proceedings of the Ninth Forest Service Remote Sensing Applications Conference, Greer, J. (ed.). ASPRS, San Diego, California.
- Key, C.H., and N.C. Benson. 2002. Measuring and remote sensing of burn severity, U.S. Geological Survey wildland fire workshop.
- Thode, A. 2005. Quantifying the fire regime attributes of severity and spatial complexity using field and imagery data, PhD diss, University of California, Davis, California.
Cited by
Sorted by citations
Items 501–600 of 1,000
Bright, B. C., Hudak, A. T., Kennedy, R. E., & Meddens, A. J. H. (2014) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2014.2346955 · Cited by 32
Raymond, C. L., Healey, S. P., Peduzzi, A., & Patterson, P. L. (2014) · Forest Ecology and Management · doi:10.1016/j.foreco.2014.09.038 · Cited by 31
Becker, K. M. L., & Lutz, J. A. (2016) · Ecosphere · doi:10.1002/ecs2.1484 · Cited by 32
Recovery of biological soil crust richness and cover 12–16 years after wildfires in Idaho, USA
Root, H. T., Brinda, J. C., & Dodson, E. K. (2017) · Biogeosciences · doi:10.5194/bg-14-3957-2017 · Cited by 31
Ricca, M. A., & Coates, P. S. (2020) · Frontiers in Ecology and Evolution · doi:10.3389/fevo.2019.00493 · Cited by 35
Zhong, S., Yu, L., Heilman, W. E., Bian, X., & Fromm, H. (2020) · Theoretical and Applied Climatology · doi:10.1007/s00704-020-03235-y · Cited by 33
Boag, A. E., Ducey, M. J., Palace, M., & Hartter, J. (2020) · Forest Ecology and Management · doi:10.1016/j.foreco.2020.118312 · Cited by 31
The effectiveness of fuel reduction burning for wildfire mitigation in sclerophyll forests
Hislop, S., Stone, C., Haywood, A., & Skidmore, A. K. (2020) · Australian Forestry · doi:10.1080/00049158.2020.1835032 · Cited by 31
Intermediate fire severity diversity promotes richness of forest carnivores in California
Furnas, B. J., Goldstein, B. R., & Figura, P. J. (2021) · Diversity and Distributions · doi:10.1111/ddi.13374 · Cited by 33
Sleeter, B. M., Frid, L., Rayfield, B., Daniel, C. J., Zhu, Z., & Marvin, D. C. (2022) · Carbon Balance and Management · doi:10.1186/s13021-022-00201-1 · Cited by 31
Self-citationWildfire burn severity and emissions inventory: an example implementation over California
Xu, Q., Westerling, A. L., Notohamiprodjo, A., Wiedinmyer, C., Picotte, J. J., Parks, S. A., Hurteau, M. D., Marlier, M. E., Kolden, C. A., Sam, J. A., et al. (2022) · Environmental Research Letters · doi:10.1088/1748-9326/ac80d0 · Cited by 36
Chen, X., Liu, S., Zhu, Z., Vogelmann, J. E., Li, Z., & Ohlen, D. O. (2009) · Ecological Indicators · doi:10.1016/j.ecolind.2009.03.013 · Cited by 31
Self-citationRickbeil, G. J. M., Hermosilla, T., Coops, N. C., White, J. C., & Wulder, M. A. (2016) · Global Change Biology · doi:10.1111/gcb.13456 · Cited by 31
Miller, M. E., Elliot, W. J., Billmire, M., Robichaud, P. R., & Endsley, K. A. (2016) · International Journal of Wildland Fire · doi:10.1071/wf15162 · Cited by 30
A review of wildfire impacts on stream temperature and turbidity across scales
Chen, J., & Chang, H. (2022) · Progress in Physical Geography Earth and Environment · doi:10.1177/03091333221118363 · Cited by 37
Stevens‐Rumann, C. S., Morgan, P., & Hoffman, C. M. (2015) · Ecosphere · doi:10.1890/es14-00443.1 · Cited by 29
Precipitation regime classification for the Mojave Desert: Implications for fire occurrence
Tagestad, J., Brooks, M. L., Cullinan, V. I., Downs, J. L., & McKinley, R. (2015) · Journal of Arid Environments · doi:10.1016/j.jaridenv.2015.09.002 · Cited by 30
Wagenbrenner, N. S., Chung, S. H., & Lamb, B. (2017) · Elementa Science of the Anthropocene · doi:10.1525/elementa.185 · Cited by 30
Effects of climate oscillations on wildland fire potential in the continental United States
Mason, S. A., Hamlington, P. E., Hamlington, B. D., Jolly, W. M., & Hoffman, C. M. (2017) · Geophysical Research Letters · doi:10.1002/2017gl074111 · Cited by 30
Lewis, S. A., Hudak, A. T., Robichaud, P. R., Morgan, P., Satterberg, K. L., Strand, E. K., Smith, A. M. S., Zamudio, J. A., & Lentile, L. B. (2017) · International Journal of Wildland Fire · doi:10.1071/wf17019 · Cited by 30
Malone, S. L., Fornwalt, P. J., Battaglia, M. A., Chambers, M. E., Iniguez, J. M., & Sieg, C. H. (2018) · Forests · doi:10.3390/f9010045 · Cited by 29
Wildfire Trend Analysis over the Contiguous United States Using Remote Sensing Observations
Salguero, J., Li, J., Farahmand, A., & Reager, J. T. (2020) · Remote Sensing · doi:10.3390/rs12162565 · Cited by 33
Fires Represent an Important Source of Carbon Emissions in Mexico
Corona-Núñez, R. O., Li, F., & Campo, J. (2020) · Global Biogeochemical Cycles · doi:10.1029/2020gb006815 · Cited by 31
Mason, D. S., & Lashley, M. A. (2021) · Fire Ecology · doi:10.1186/s42408-020-00087-9 · Cited by 30
Ebel, B. A., Moody, J. A., & Martin, D. A. (2021) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2021.149847 · Cited by 30
Reilly, S., Clark, M. L., Bentley, L. P., Matley, C., Piazza, E., & Menor, I. O. (2021) · Remote Sensing · doi:10.3390/rs13193810 · Cited by 31
Beyene, M. T., Leibowitz, S. G., Dunn, C. J., & Bladon, K. D. (2022) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2022.160731 · Cited by 33
Mangeon, S., Field, R. D., Fromm, M. D., McHugh, C. W., & Voulgarakis, A. (2015) · The Anthropocene Review · doi:10.1177/2053019615588790 · Cited by 30
Burn severity controls on postfire Araucaria‐Nothofagus regeneration in the Andean Cordillera
Assal, T. J., González, M. E., & Sibold, J. S. (2018) · Journal of Biogeography · doi:10.1111/jbi.13428 · Cited by 29
A robust visible near-infrared index for fire severity mapping in Arctic tundra ecosystems
Chen, Y., Lara, M. J., & Hu, F. S. (2019) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2019.11.012 · Cited by 30
Yu, G., Feng, Y. W., Wang, J., & Wright, D. B. (2023) · Earth s Future · doi:10.1029/2023ef003823 · Cited by 32
Mpakairi, K. S., Ndaimani, H., & Kavhu, B. (2020) · Scientific African · doi:10.1016/j.sciaf.2020.e00565 · Cited by 29
Chen, D., Fu, C., Hall, J., Hoy, E., & Loboda, T. V. (2021) · Remote Sensing of Environment · doi:10.1016/j.rse.2021.112393 · Cited by 30
Wang, J., Xiaoyang Zhang, A., & Rodman, K. C. (2021) · Agricultural and Forest Meteorology · doi:10.1016/j.agrformet.2021.108432 · Cited by 28
Coop, J. D. (2022) · Ecological Applications · doi:10.1002/eap.2725 · Cited by 29
Rodman, K. C., Andrus, R. A., Carlson, A. R., Carter, T., Chapman, T. B., Coop, J. D., Fornwalt, P. J., Gill, N. S., Harvey, B. J., Hoffman, A. E., et al. (2022) · Journal of Ecology · doi:10.1111/1365-2745.13999 · Cited by 29
Detecting post-fire salvage logging from Landsat change maps and national fire survey data
Schroeder, T. A., Wulder, M. A., Healey, S. P., & Moisen, G. G. (2012) · Remote Sensing of Environment · doi:10.1016/j.rse.2011.10.031 · Cited by 29
Cohen, J. J., Blinn, C. E., Boyle, K., Holmes, T. P., & Moeltner, K. (2014) · Environmental and Resource Economics · doi:10.1007/s10640-014-9856-y · Cited by 29
McCarley, T. R., Kolden, C. A., Vaillant, N. M., Hudak, A. T., Smith, A. M. S., & Kreitler, J. R. (2017) · Forest Ecology and Management · doi:10.1016/j.foreco.2017.02.015 · Cited by 29
Recent post-wildfire salvage logging benefits local and landscape floral and bee communities
Heil, L. J., & Burkle, L. A. (2018) · Forest Ecology and Management · doi:10.1016/j.foreco.2018.05.009 · Cited by 28
Tillery, A. C., Haas, J. R., Miller, L. W., Scott, J. H., & Thompson, M. P. (2014) · Scientific Investigations Report · doi:10.3133/sir20145161 · Cited by 30
Spatial wildfire occurrence data for the United States, 1992-2018 [FPA_FOD_20210617] (5th Edition)
Short, K. C. (2021) · Forest Service Research Data Archive · doi:10.2737/rds-2013-0009.5 · Cited by 29
Country-level fire perimeter datasets (2001–2021)
Mahood, A. L., Lindrooth, E. J., Cook, M., & Balch, J. K. (2022) · Scientific Data · doi:10.1038/s41597-022-01572-3 · Cited by 30
Rodman, K. C., Davis, K. T., Parks, S. A., Chapman, T. B., Coop, J. D., Iniguez, J. M., Roccaforte, J. P., Meador, A. J. S., Springer, J. D., Stevens‐Rumann, C. S., et al. (2023) · Global Change Biology · doi:10.1111/gcb.16939 · Cited by 29
Busby, S. U., Evers, C., & Holz, A. (2024) · Ecosphere · doi:10.1002/ecs2.4805 · Cited by 28
Wang, J., & Zhang, X. (2017) · Environmental Research Letters · doi:10.1088/1748-9326/aa6ad9 · Cited by 31
Ebel, B. A., Romero, O. C., & Martin, D. A. (2018) · Hydrological Processes · doi:10.1002/hyp.13167 · Cited by 27
Wilmot, T. Y., Hallar, A. G., Lin, J. C., & Mallia, D. V. (2021) · Environmental Research Letters · doi:10.1088/1748-9326/abf966 · Cited by 28
Buch, J., Williams, P., Juang, C. S., Hansen, W. D., & Gentine, P. (2023) · Geoscientific model development · doi:10.5194/gmd-16-3407-2023 · Cited by 33
Francis, E. J., Pourmohammadi, P., Steel, Z. L., Collins, B. M., & Hurteau, M. D. (2023) · Landscape Ecology · doi:10.1007/s10980-023-01710-1 · Cited by 30
What Drives Low-Severity Fire in the Southwestern USA?
Parks, S. A., Dobrowski, S. Z., & Panunto, M. H. (2018) · Forests · doi:10.3390/f9040165 · Cited by 28
Villarreal, M. L., Haire, S. L., Iniguez, J. M., Montaño, C. C., & Poitras, T. B. (2019) · Fire Ecology · doi:10.1186/s42408-018-0012-x · Cited by 28
Assessing Landscape Vulnerability to Wildfire in the USA
Vaillant, N. M., Kolden, C. A., & Smith, A. M. S. (2016) · Current Forestry Reports · doi:10.1007/s40725-016-0040-1 · Cited by 28
Bouchard, M., Butman, D., Hawbaker, T. J., Li, Z., Liu, J., Liu, S., McDonald, C. P., Reker, R. R., Sayler, K. L., Sleeter, B. M., et al. (2011) · USGS professional paper · doi:10.3133/pp1787 · Cited by 28
Self-citationMultitemporal lidar captures heterogeneity in fuel loads and consumption on the Kaibab Plateau
Bright, B. C., Hudak, A. T., McCarley, T. R., Spannuth, A., Sánchez‐López, N., Ottmar, R. D., & Soja, A. J. (2022) · Fire Ecology · doi:10.1186/s42408-022-00142-7 · Cited by 27
Previous fires and roads limit wildfire growth in Arizona and New Mexico, U.S.A.
Yocom, L. L., Jenness, J., Fulé, P. Z., & Thode, A. E. (2019) · Forest Ecology and Management · doi:10.1016/j.foreco.2019.06.037 · Cited by 30
Structural diversity and development in active fire regime mixed-conifer forests
Berkey, J. K., Belote, R. T., Maher, C. T., & Larson, A. J. (2020) · Forest Ecology and Management · doi:10.1016/j.foreco.2020.118548 · Cited by 27
Wildfire impacts on the persistent suspended sediment dynamics of the Ventura River, California
Jumps, N. I., Gray, A. B., Guilinger, J. J., & Cowger, W. (2022) · Journal of Hydrology Regional Studies · doi:10.1016/j.ejrh.2022.101096 · Cited by 27
Li, Z., Angerer, J. P., & Wu, X. B. (2022) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2022.157214 · Cited by 31
Perrault-Hébert, M., Boucher, Y., Fournier, R., Girard, F., Auger, I., Thiffault, N., & Grenon, F. (2017) · Forest Ecology and Management · doi:10.1016/j.foreco.2017.05.026 · Cited by 27
Hamilton, M., Nielsen‐Pincus, M., & Evers, C. (2023) · Ecology and Society · doi:10.5751/es-13856-280303 · Cited by 28
Scaling-up ecological understanding with remote sensing and causal inference
Cleemput, E. V., Adler, P. B., Suding, K. N., Rebelo, A. J., Poulter, B., & Dee, L. E. (2024) · Trends in Ecology & Evolution · doi:10.1016/j.tree.2024.09.006 · Cited by 27
How do plant communities differ between fire refugia and fire‐generated early‐seral vegetation?
Downing, W. M., Krawchuk, M. A., Coop, J. D., Meigs, G. W., Haire, S. L., Walker, R. B., Whitman, E., Chong, G. W., Miller, C., & Tortorelli, C. M. (2019) · Journal of Vegetation Science · doi:10.1111/jvs.12814 · Cited by 26
PEMIP: Post-fire erosion model inter-comparison project
Kampf, S. K., Gannon, B. M., Wilson, C., Saavedra, F. A., Miller, M. E., Heldmyer, A. J., Livneh, B., Nelson, P. A., & MacDonald, L. H. (2020) · Journal of Environmental Management · doi:10.1016/j.jenvman.2020.110704 · Cited by 26
Strong Legacy Effects of Prior Burn Severity on Forest Resilience to a High-Severity Fire
Harris, L. B., Drury, S. A., & Taylor, A. H. (2020) · Ecosystems · doi:10.1007/s10021-020-00548-x · Cited by 26
Extent of Recent Fire-Induced Losses of Ponderosa Pine Forests of the Southwestern UsPreprint
Woolman, A., Coop, J. D., Shaw, J. D., & DeMarco, J. (2022) · SSRN Electronic Journal · doi:10.1016/j.foreco.2022.120381 · Cited by 28
Braziunas, K. H., Kiel, N. G., & Turner, M. G. (2023) · Ecology · doi:10.1002/ecy.4042 · Cited by 27
Berner, L. T., & Law, B. E. (2015) · Biogeosciences · doi:10.5194/bg-12-6617-2015 · Cited by 26
Vanderhoof, M. K., Williams, C. A., Shuai, Y., Jarvis, D., Kulakowski, D., & Masek, J. G. (2014) · Biogeosciences · doi:10.5194/bg-11-563-2014 · Cited by 25
Landscape-Scale Vegetation Change Following Fire in Point Reyes, California, USA
Forrestel, A. B., Moritz, M. A., & Stephens, S. L. (2011) · Fire Ecology · doi:10.4996/fireecology.0702114 · Cited by 26
Is proportion burned severely related to daily area burned?
Birch, D. S., Morgan, P., Kolden, C. A., Hudak, A. T., & Smith, A. M. S. (2014) · Environmental Research Letters · doi:10.1088/1748-9326/9/6/064011 · Cited by 26
Tracy, J. L., Trabucco, A., Lawing, A. M., Giermakowski, J. T., Tchakerian, M. D., Drus, G. M., & Coulson, R. N. (2018) · Ecological Modelling · doi:10.1016/j.ecolmodel.2018.05.019 · Cited by 26
Vulnerability of Physically Protected Soil Organic Carbon to Loss Under Low Severity Fires
Jian, M., Berhe, A. A., Berli, M., & Ghezzehei, T. A. (2018) · Frontiers in Environmental Science · doi:10.3389/fenvs.2018.00066 · Cited by 26
Gendaszek, A. S., Dunham, J. B., Torgersen, C. E., Hockman-Wert, D. P., Heck, M. P., Thorson, J. M., Mintz, J., & Allai, T. (2020) · Water · doi:10.3390/w12071962 · Cited by 26
Reilly, M. J., Zuspan, A., & Yang, Z. (2023) · Fire Ecology · doi:10.1186/s42408-023-00223-1 · Cited by 25
Logistic regression versus XGBoost for detecting burned areas using satellite images
Militino, A. F., Goyena, H., Pérez-Goya, U., & Ugarte, M. (2024) · Environmental and Ecological Statistics · doi:10.1007/s10651-023-00590-7 · Cited by 23
West, A. M., Kumar, S., & Jarnevich, C. S. (2015) · Climatic Change · doi:10.1007/s10584-015-1553-5 · Cited by 25
McCarley, T. R., Smith, A. M. S., Kolden, C. A., & Kreitler, J. R. (2018) · International Journal of Wildland Fire · doi:10.1071/wf17137 · Cited by 25
High fire disturbance in forests leads to longer recovery, but varies by forest type
Hislop, S., Jones, S., Soto‐Berelov, M., Skidmore, A. K., Haywood, A., & Trung, N. H. (2019) · Remote Sensing in Ecology and Conservation · doi:10.1002/rse2.113 · Cited by 25
Colorado River water supply is predictable on multi-year timescales owing to long-term ocean memory
Chikamoto, Y., Wang, S., Yost, M. A., Yocom, L. L., & Gillies, R. R. (2020) · Communications Earth & Environment · doi:10.1038/s43247-020-00027-0 · Cited by 25
Singleton, M. P., Thode, A. E., Meador, A. J. S., Iniguez, J. M., & Stevens, J. T. (2021) · Landscape Ecology · doi:10.1007/s10980-021-01318-3 · Cited by 25
Collar, N. M., Saxe, S., Rust, A. J., & Hogue, T. S. (2021) · Journal of Hydrology · doi:10.1016/j.jhydrol.2021.127162 · Cited by 25
Weise, C. L., Brussee, B. E., Coates, P. S., Shinneman, D. J., Crist, M. R., Aldridge, C. L., Heinrichs, J. A., & Ricca, M. A. (2023) · Journal of Environmental Management · doi:10.1016/j.jenvman.2023.117903 · Cited by 25
Arnold, J. D., Brewer, S., & Dennison, P. E. (2014) · Fire Ecology · doi:10.4996/fireecology.1002064 · Cited by 25
Su, Y., Bales, R. C., Ma, Q., Nydick, K. R., Ray, R. L., Li, W., & Guo, Q. (2017) · Journal of Geophysical Research Biogeosciences · doi:10.1002/2017jg004005 · Cited by 25
Hagmann, R. K., Merschel, A. G., & Reilly, M. J. (2019) · Landscape Ecology · doi:10.1007/s10980-019-00791-1 · Cited by 26
Sources and implications of bias and uncertainty in a century of us wildfire activity data
Short, K. C. (2014) · Imprensa da Universidade de Coimbra eBooks · doi:10.14195/978-989-26-0884-6_167 · Cited by 25
Reconstructing Landscape Pattern of Historical Fires and Fire Regimes
Swetnam, T. L., Falk, D. A., Hessl, A., & Farris, C. A. (2010) · Ecological studies · doi:10.1007/978-94-007-0301-8_7 · Cited by 25
Effects of Wildfire Destruction on Migration, Consumer Credit, and Financial Distress
McConnell, K., Whitaker, S. D., Fussell, E., DeWaard, J., Curtis, K. J., Price, K., Denis, L. S., & Balch, J. K. (2021) · Working paper · doi:10.26509/frbc-wp-202129 · Cited by 27
Land and Atmosphere Precursors to Fuel Loading, Wildfire Ignition and Post‐Fire Recovery
Alizadeh, M., Adamowski, J., & Entekhabi, D. (2024) · Geophysical Research Letters · doi:10.1029/2023gl105324 · Cited by 21
Trotta, G., Cadez, L., Boscutti, F., Vuerich, M., Asquini, E., Boscarol, G., Cingano, P., Azzani, G., Pischedda, S., Tomao, A., et al. (2024) · Fire Ecology · doi:10.1186/s42408-024-00330-7 · Cited by 25
Green is the New Black: Outcomes of post-fire tree planting across the US Interior West
Rodman, K. C., Fornwalt, P. J., Holden, Z. A., Crouse, J. E., Davis, K. T., Marshall, L. A. E., Stoddard, M. T., Andrus, R. A., Chambers, M. E., Chapman, T. B., et al. (2024) · Forest Ecology and Management · doi:10.1016/j.foreco.2024.122358 · Cited by 24
Characterizing Spatial Neighborhoods of Refugia Following Large Fires in Northern New Mexico USA
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Talucci, A. C., Lertzman, K. P., & Krawchuk, M. (2019) · Forest Ecology and Management · doi:10.1016/j.foreco.2019.117500 · Cited by 21
Kovács, K. D. (2019) · Geographia Technica · doi:10.21163/gt_2019.142.03 · Cited by 24
Rhea, A. E., Covino, T. P., & Rhoades, C. C. (2021) · Journal of Geophysical Research Biogeosciences · doi:10.1029/2020jg006095 · Cited by 28
Fire‐Induced Carbon Loss and Tree Mortality in Siberian Larch Forests
Webb, E. E., Alexander, H. D., Paulson, A. K., Loranty, M. M., DeMarco, J., Talucci, A. C., Spektor, V. V., Zimov, N., & Lichstein, J. W. (2024) · Geophysical Research Letters · doi:10.1029/2023gl105216 · Cited by 24
Drury, S. A., Larkin, N., Strand, T. T., Huang, S., Strenfel, S. J., Banwell, E. M., O’Brien, T. E., & Raffuse, S. M. (2014) · Fire Ecology · doi:10.4996/fireecology.1001056 · Cited by 24
Huffman, D., Crouse, J., Meador, A. J. S., Springer, J., & Stoddard, M. (2018) · Forest Ecology and Management · doi:10.1016/j.foreco.2017.10.032 · Cited by 22
Gray, M. E., Zachmann, L. J., & Dickson, B. G. (2018) · Earth system science data · doi:10.5194/essd-10-1715-2018 · Cited by 26
Metadata
- Authors
- Eidenshink, J., Schwind, B., Brewer, K., Zhu, Z.-L., Quayle, B., & Howard, S.
- Affiliations
- United States Geological Survey (US)
- US Forest Service (US)
- Corresponding author
- Eidenshink, Jeff
- ORCID
- Howard, Stephen
- Venue
- Fire Ecology
- Published
- 2007-06
- Volume
- 3
- Issue
- 1
- Pages
- 3-21
- ISSN
- 1933-9747 (ISSN-L)
- OpenAlex
- W2138800506
- Cited by
- 1,423
- References
- 31
- Citations by year
- 2026: 110 · 2025: 118 · 2024: 138 · 2023: 101 · 2022: 123 · 2021: 96 · 2020: 111 · 2019: 112 · 2018: 100 · 2017: 73 · 2016: 65 · 2015: 77 · 2014: 64 · 2013: 42 · 2012: 42
- FWCI
- 6.16
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Fire Ecology (publishedVersion, cc-by)
- Funders
- U.S. Department of Agriculture
- U.S. Forest Service
- Topics
- Physical Sciences › Environmental Science › Global and Planetary Change › Fire effects on ecosystems
- Physical Sciences › Environmental Science › Ecology › Rangeland and Wildlife Management
- Health Sciences › Medicine › Surgery › Burn Injury Management and Outcomes
- Keywords
- burn severity, Monitoring Trends in Burn Severity, National Fire Plan, forest fires, dNBR, Landsat, fire policy, fire risk assessment
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